Vehicle routing and crew scheduling for metropolitan mail distribution at Australia Post

This paper presents a new multi-depot combined vehicle and crew scheduling algorithm, and uses it, in conjunction with a heuristic vehicle routing algorithm, to solve the intra-city mail distribution problem faced by Australia Post. First we describe the Australia Post mail distribution problem and outline the heuristic vehicle routing algorithm used to find vehicle routes. We present a new multi-depot combined vehicle and crew scheduling algorithm based on set covering with column generation. The paper concludes with a computational investigation examining the affect of different types of vehicle routing solutions on the vehicle and crew scheduling solution, comparing the different levels of integration possible with the new vehicle and crew scheduling algorithm and comparing the results of sequential versus simultaneous vehicle and crew scheduling, using real life data for Australia Post distribution networks.

A monolithic smoothing-gap algorithm for contact-impact based on the signed distance function

A new algorithm has been developed for smoothing the surfaces in finite element formulations of contact-impact. A key feature of this method is that the smoothing is done implicitly by constructing smooth signed distance functions for the bodies. These functions are then employed for the computation of the gap and other variables needed for implementation of contact-impact. The smoothed signed distance functions are constructed by a moving least-squares approximation with a polynomial basis. Results show that when nodes are placed on a surface, the surface can be reproduced with an error of about one per cent or less with either a quadratic or a linear basis. With a quadratic basis, the method exactly reproduces a circle or a sphere even for coarse meshes. Results are presented for contact problems involving the contact of circular bodies. Copyright (C) 2002 John Wiley Sons, Ltd.

GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA

Background: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA structure and flexibility may also play a role in protein-DNA interactions, the simultaneous exploration of sequence-and structure-based hypotheses about the composition of binding sites and the ordering of features in a regulatory region should be considered as well. The consideration of structural features requires the development of new detection tools that can deal with data types other than primary sequence. Results: GANN ( available at http://bioinformatics.org.au/gann) is a machine learning tool for the detection of conserved features in DNA. The software suite contains programs to extract different regions of genomic DNA from flat files and convert these sequences to indices that reflect sequence and structural composition or the presence of specific protein binding sites. The machine learning component allows the classification of different types of sequences based on subsamples of these indices, and can identify the best combinations of indices and machine learning architecture for sequence discrimination. Another key feature of GANN is the replicated splitting of data into training and test sets, and the implementation of negative controls. In validation experiments, GANN successfully merged important sequence and structural features to yield good predictive models for synthetic and real regulatory regions. Conclusion: GANN is a flexible tool that can search through large sets of sequence and structural feature combinations to identify those that best characterize a set of sequences.

A first-principles density-functional calculation of the electronic and vibrational structure of the key melanin monomers

We report first-principles density-functional calculations for hydroquinone (HQ), indolequinone (IQ), and semiquinone (SQ). These molecules are believed to be the basic building blocks of the eumelanins, a class of biomacromolecules with important biological functions (including photoprotection) and with the potential for certain bioengineering applications. We have used the difference of self-consistent fields method to study the energy gap between the highest occupied molecular orbital and the lowest unoccupied molecular orbital, HL. We show that HL is similar in IQ and SQ, but approximately twice as large in HQ. This may have important implications for our understanding of the observed broadband optical absorption of the eumelanins. The possibility of using this difference in HL to molecularly engineer the electronic properties of eumelanins is discussed. We calculate the infrared and Raman spectra of the three redox forms from first principles. Each of the molecules have significantly different infrared and Raman signatures, and so these spectra could be used in situ to nondestructively identify the monomeric content of macromolecules. It is hoped that this may be a helpful analytical tool in determining the structure of eumelanin macromolecules and hence in helping to determine the structure-property-function relationships that control the behavior of the eumelanins.

Embedded Voxel Colouring

The reconstruction of a complex scene from multiple images is a fundamental problem in the field of computer vision. Volumetric methods have proven to be a strong alternative to traditional correspondence-based methods due to their flexible visibility models. In this paper we analyse existing methods for volumetric reconstruction and identify three key properties of voxel colouring algorithms: a water-tight surface model, a monotonic carving order, and causality. We present a new Voxel Colouring algorithm which embeds all reconstructions of a scene into a single output. While modelling exact visibility for arbitrary camera locations, Embedded Voxel Colouring removes the need for a priori threshold selection present in previous work. An efficient implementation is given along with results demonstrating the advantages of posteriori threshold selection.

An improved seeded region growing algorithm

Recently Adams and Bischof (1994) proposed a novel region growing algorithm for segmenting intensity images. The inputs to the algorithm are the intensity image and a set of seeds - individual points or connected components - that identify the individual regions to be segmented. The algorithm grows these seed regions until all of the image pixels have been assimilated. Unfortunately the algorithm is inherently dependent on the order of pixel processing. This means, for example, that raster order processing and anti-raster order processing do not, in general, lead to the same tessellation. In this paper we propose an improved seeded region growing algorithm that retains the advantages of the Adams and Bischof algorithm fast execution, robust segmentation, and no tuning parameters - but is pixel order independent. (C) 1997 Elsevier Science B.V.

A phylogenetic study of Lepidapedoides Yamaguti, 1970 (Digenea) with a key and descriptions of two new species from western Australia

Two new species of the genus Lepidapedoides are described from the aulopodid teleost Aulopus purpurissatus from south-western Australia. Both are distinguished from other Lepidapedoides spp. by their pedunculate ventral sucker. Lepidapedoides pistoris n. sp. and L. elongatrium n. sp. are distinguished by the possession of a narrow, elongate form, a long ventral sucker to ovary distance: the vitellarium reaching only to the posterior level of the cirrus-sac, the cirrus-sac length and the deep genital atrium with the metraterm entering distally to its base in L. elongatrium. A key to species of the genus is given. A character matrix is included for the genus. Poorly resolved phylogenetic trees indicate two main lineages in the genus. The two new species described here are resolved as sister taxa. The new combination Lepidapedoides freitasi (Kohn gr Fernandes, 1970) is formed for Acanthocolpoides freitasi.

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.

Key residues characteristic of GATA N-fingers are recognized by FOG

Protein-protein interactions play significant roles in the control of gene expression. These interactions often occur between small, discrete domains within different transcription factors. In particular, zinc fingers, usually regarded as DNA-binding domains, are now also known to be involved in mediating contacts between proteins. We have investigated the interaction between the erythroid transcription factor GATA-1 and its partner, the 9 zinc finger protein, FOG (Friend of GATA). We demonstrate that this interaction represents a genuine finger-finger contact, which is dependent on zinc coordinating residues within each protein. We map the contact domains to the core of the N-terminal zinc finger of GATA-1 and the 6th zinc finger of FOG. Using a scanning substitution strategy we identify key residues within the GATA-1 N-finger which are required for FOG binding. These residues are conserved in the N-fingers of all GATA proteins known to bind FOG, but are not found in the respective C-fingers, This observation may, therefore, account for the particular specificity of FOG for N-fingers, Interestingly, the key N-finger residues are seen to form a contiguous surface, when mapped onto the structure of the N-finger of GATA-1.

A consistent point-searching algorithm for solution interpolation in unstructured meshes consisting of 4-node bilinear quadrilateral elements

To translate and transfer solution data between two totally different meshes (i.e. mesh 1 and mesh 2), a consistent point-searching algorithm for solution interpolation in unstructured meshes consisting of 4-node bilinear quadrilateral elements is presented in this paper. The proposed algorithm has the following significant advantages: (1) The use of a point-searching strategy allows a point in one mesh to be accurately related to an element (containing this point) in another mesh. Thus, to translate/transfer the solution of any particular point from mesh 2 td mesh 1, only one element in mesh 2 needs to be inversely mapped. This certainly minimizes the number of elements, to which the inverse mapping is applied. In this regard, the present algorithm is very effective and efficient. (2) Analytical solutions to the local co ordinates of any point in a four-node quadrilateral element, which are derived in a rigorous mathematical manner in the context of this paper, make it possible to carry out an inverse mapping process very effectively and efficiently. (3) The use of consistent interpolation enables the interpolated solution to be compatible with an original solution and, therefore guarantees the interpolated solution of extremely high accuracy. After the mathematical formulations of the algorithm are presented, the algorithm is tested and validated through a challenging problem. The related results from the test problem have demonstrated the generality, accuracy, effectiveness, efficiency and robustness of the proposed consistent point-searching algorithm. Copyright (C) 1999 John Wiley & Sons, Ltd.

MiAMP1, a novel protein from Macadamia integrifolia adopts a Greek key beta-barrel fold unique amongst plant antimicrobial proteins

MiAMP1 is a recently discovered 76 amino acid residue, highly basic protein from the nut kernel of:Macadamia integrifolia which possesses no sequence homology to any known protein and inhibits the growth of several microbial plant pathogens in vitro while having no effect on mammalian or plant cells. It is considered to be a potentially useful tool for the genetic engineering of disease resistance in transgenic crop plants and for the design of new fungicides. The three-dimensional structure of MiAMP1 was determined through homonuclear and heteronuclear (N-15) 2D NMR spectroscopy and subsequent simulated annealing calculations with the ultimate aim of understanding the structure-activity relationships of the protein. MiAMP1 is made up of eight beta-strands which are arranged in two Greek key motifs. These Greek key motifs associate to form a Greek key beta-barrel. This structure is unique amongst plant antimicrobial proteins and forms a new class which we term the beta-barrelins. Interestingly, the structure of MiAMP1 bears remarkable similarity to a yeast killer toxin from Williopsis mrakii. This toxin acts by inhibiting beta-glucan synthesis and thereby cell wall construction in sensitive strains of yeast. The structural similarity of MiAMP1 and WmKT, which originate from plant and fungal phyla respectively, may reflect a similar mode of action. (C) 1999 Academic Press.

Trial-of-antibiotic algorithm for the diagnosis of tuberculosis in a district hospital in a developing country with high HIV prevalence

OBJECTIVE: To evaluate a diagnostic algorithm for pulmonary tuberculosis based on smear microscopy and objective response to trial of antibiotics. SETTING: Adult medical wards, Hlabisa Hospital, South Africa, 1996-1997. METHODS: Adults with chronic chest symptoms and abnormal chest X-ray had sputum examined for Ziehl-Neelsen stained acid-fast bacilli by light microscopy. Those with negative smears were treated with amoxycillin for 5 days and assessed. Those who had not improved were treated with erythromycin for 5 days and reassessed. Response was compared with mycobacterial culture. RESULTS: Of 280 suspects who completed the diagnostic pathway, 160 (57%) had a positive smear, 46 (17%) responded to amoxycillin, 34 (12%) responded to erythromycin and 40 (14%) were treated as smear-negative tuberculosis. The sensitivity (89%) and specificity (84%) of the full algorithm for culture-positive tuberculosis were high. However, 11 patients (positive predictive value [PPV] 95%) were incorrectly diagnosed with tuberculosis, and 24 cases of tuberculosis (negative predictive value [NPV] 70%) were not identified. NPV improved to 75% when anaemia was included as a predictor. Algorithm performance was independent of human immunodeficiency virus status. CONCLUSION: Sputum smear microscopy plus trial of antibiotic algorithm among a selected group of tuberculosis suspects may increase diagnostic accuracy in district hospitals in developing countries.

Minimum-order stable recursive filter design via the genetic algorithm approach

In this paper, the minimum-order stable recursive filter design problem is proposed and investigated. This problem is playing an important role in pipeline implementation sin signal processing. Here, the existence of a high-order stable recursive filter is proved theoretically, in which the upper bound for the highest order of stable filters is given. Then the minimum-order stable linear predictor is obtained via solving an optimization problem. In this paper, the popular genetic algorithm approach is adopted since it is a heuristic probabilistic optimization technique and has been widely used in engineering designs. Finally, an illustrative example is sued to show the effectiveness of the proposed algorithm.

An equivalent algorithm for simulating thermal effects of magma intrusion problems in porous rocks

An equivalent algorithm is proposed to simulate thermal effects of the magma intrusion in geological systems, which are composed of porous rocks. Based on the physical and mathematical equivalence, the original magma solidification problem with a moving boundary between the rock and intruded magma is transformed into a new problem without the moving boundary but with a physically equivalent heat source. From the analysis of an ideal solidification model, the physically equivalent heat source has been determined in this paper. The major advantage in using the proposed equivalent algorithm is that the fixed finite element mesh with a variable integration time step can be employed to simulate the thermal effect of the intruded magma solidification using the conventional finite element method. The related numerical results have demonstrated the correctness and usefulness of the proposed equivalent algorithm for simulating the thermal effect of the intruded magma solidification in geological systems. (C) 2003 Elsevier B.V. All rights reserved.

A new algorithm and refined bounds for extended gcd computation

Extended gcd computation is interesting itself. It also plays a fundamental role in other calculations. We present a new algorithm for solving the extended gcd problem. This algorithm has a particularly simple description and is practical. It also provides refined bounds on the size of the multipliers obtained.